AMR Country Hotspots

##  Family: zero_inflated_poisson 
##   Links: mu = log; zi = logit 
## Formula: n_amr_events ~ ln_livestock_consumption_kg_per_capita + ln_migrant_pop_perc + ln_tourism_inbound_perc + ab_export_perc + health_expend_perc + human_consumption_ddd + english_spoken + ln_pubs_sum_per_capita + ln_promed_mentions_per_capita + ln_gdp_per_capita + offset(ln_population) 
##          zi ~ ln_pubs_sum_per_capita + ln_promed_mentions_per_capita + ln_gdp_per_capita + ln_population + english_spoken
##    Data: data[[i]] (Number of observations: 198) 
## Samples: 120 chains, each with iter = 2000; warmup = 1000; thin = 1;
##          total post-warmup samples = 120000
## 
## Population-Level Effects: 
##                                        Estimate Est.Error l-95% CI
## Intercept                                -13.80      2.76   -19.51
## zi_Intercept                              29.66      6.97    16.72
## ln_livestock_consumption_kg_per_capita    -0.41      0.16    -0.61
## ln_migrant_pop_perc                        0.21      0.07     0.09
## ln_tourism_inbound_perc                    0.12      0.08    -0.02
## ab_export_perc                             5.36      1.10     3.05
## health_expend_perc                         0.02      0.02    -0.03
## human_consumption_ddd                      0.10      0.02     0.07
## english_spoken                            -0.55      0.14    -0.80
## ln_pubs_sum_per_capita                     0.12      0.11    -0.09
## ln_promed_mentions_per_capita              0.25      0.09     0.08
## ln_gdp_per_capita                         -0.05      0.12    -0.26
## zi_ln_pubs_sum_per_capita                 -0.07      0.29    -0.65
## zi_ln_promed_mentions_per_capita           0.16      0.34    -0.50
## zi_ln_gdp_per_capita                      -1.33      0.30    -1.95
## zi_ln_population                          -1.03      0.23    -1.50
## zi_english_spoken                         -1.51      0.66    -2.85
##                                        u-95% CI Eff.Sample Rhat
## Intercept                                 -8.88         79 2.04
## zi_Intercept                              44.06       1968 1.02
## ln_livestock_consumption_kg_per_capita    -0.07         63 4.48
## ln_migrant_pop_perc                        0.36         75 2.27
## ln_tourism_inbound_perc                    0.25         72 2.42
## ab_export_perc                             7.41        123 1.40
## health_expend_perc                         0.06         87 1.80
## human_consumption_ddd                      0.14         73 2.35
## english_spoken                            -0.27         75 2.24
## ln_pubs_sum_per_capita                     0.32        112 1.47
## ln_promed_mentions_per_capita              0.44         75 2.25
## ln_gdp_per_capita                          0.24         77 2.12
## zi_ln_pubs_sum_per_capita                  0.49        664 1.05
## zi_ln_promed_mentions_per_capita           0.85       6053 1.01
## zi_ln_gdp_per_capita                      -0.77       1189 1.03
## zi_ln_population                          -0.59       2045 1.02
## zi_english_spoken                         -0.27       1135 1.03
## 
## Samples were drawn using sampling(NUTS). For each parameter, Eff.Sample 
## is a crude measure of effective sample size, and Rhat is the potential 
## scale reduction factor on split chains (at convergence, Rhat = 1).

## [1] TRUE